Control scheme selection in human-machine- interfaces by analysis of activity signals
Abstract: Human-Machine Interfaces in rehabilitation engineering often use activity signals. Examples are electrical wheelchairs or prostheses controlled by means of muscle contractions. Activity signals are user-dependent and often reflect neurological weaknesses. Thus, not all users are able to operate the same control scheme in a robust manner. To avoid under- and overstraining, the interface ideally uses a control scheme which reflects the user’s control ability best. Therefore, we explored typical phenomena of activation signals. We derive criteria to quantify the user’s performance and abilities and present a routine which automatically selects and adapts one of three control schemes being best suited.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Control scheme selection in human-machine- interfaces by analysis of activity signals ; volume:2 ; number:1 ; year:2016 ; pages:707-710 ; extent:4
Current directions in biomedical engineering ; 2, Heft 1 (2016), 707-710 (gesamt 4)
- Urheber
- DOI
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10.1515/cdbme-2016-0153
- URN
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urn:nbn:de:101:1-2410141656141.867916187117
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:21 MESZ
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Beteiligte
- Doneit, Wolfgang
- Mikut, Ralf
- Liebetanz, David
- Rupp, Rüdiger
- Reischl, Markus
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